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New data quality assessment tool available

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Illustrative image of FAIR Check Service showing FAIR lettering with globe and yardstick.
New data quality assessment tool available
New data quality assessment tool available

The FAIR principles are fundamental to good research data management. To help researchers apply the principles, several tools for assessing the FAIRness of data are already available (for an overview, see!/).

However, from the point of view of the cultural heritage disciplines, we found several aspects missing in these existing tools: on the one hand, they are usually quite generic and intended for all sciences and disciplines; on the other hand, the checks usually don't give concrete solutions how to improve the quality of a a certain data set. Additionally, research projects on tangible and intangible cultural heritage often face very specific situations due to work with different data formats, combined with legal and ethical challenges. A generic "ticking off" of the FAIR principles is therefore hardly possible; rather, an individual solution for the implementation of the FAIR principles is usually needed, which ideally also includes a personal discussion with experts.

Therefore, the FAIR self-check of NFDI4Culture is adapted to data from the cultural heritage sector. Links to the Guideline for a FAIR Cultural Studies Research Data Management (in German) provide more in-depth explanations and recommendations. As a result, our check does not offer a seemingly objective assessment, since the individual situation of each research project cannot be captured in form of percentages or traffic light colors. Instead, our questionnaire is intended to encourage reflection on one's own handling of research data and to point out where there are opportunities for improving data quality.

Another special feature of the FAIR Check is the integrated option to contact the NFDI4Culture Helpdesk directly with the results and questions that came up, in order to clarify specific problems in a face-to-face conversation.

Desiree Mayer
Martha Stellmacher
Task Area 2: Standards, data quality and curation